Video has for some time been, and continues to be a highly popular medium for the enjoyment of entertainment content in the form of movie, television, and sports content, for example, as well as for information content such as news. Due to its popularity with consumers, ever more video content is being produced and made available for distribution. Consequently, the accuracy and efficiency with which video content can be reviewed, classified, archived, and managed has become increasingly important to producers, owners, and distributors of such content. For example, techniques for automating the classification of video content based on features or images included in the video, may reduce the time spent in video production and management.
Unfortunately, conventional approaches to automating video classification typically require initial datasets that may be costly and time consuming to prepare. For example, conventional approaches to classifying video content based on image recognition require that collections of precisely labeled images be prepared as an initial input for comparative purposes.